Has used agenerative AImodel for anon-academicpurposeHas traveledinternationallyto attend thisconferenceHas presenteda paper onnaturallanguagegenerationIs currentlyworking on aprojectinvolving cross-lingual transferlearningIs familiarwith theconcept ofpromptengineeringHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel tocreate art ormusicHas apreferred AIresearch toolthey canrecommendHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPHassuccessfullydebugged acomplexLLMHascontributedto an open-source AIprojectIs excitedabout thepotential ofLLMs ineducationCanrecommenda good AI ortech relatedpodcastHasattended anICMLconferencebeforeCan explain thedifferencebetween causaland maskedlanguagemodelsIs optimisticabout thefuture ofhuman-AIcollaborationHas learneda newlanguage inthe last yearKnows atleast threeprogramminglanguagesHas used anLLM tosummarizeresearchpapersCan namethreedifferent LLMarchitecturesHasexperiencewith fine-tuning a pre-trained LLMHasparticipated ina hackathonfocused on AIor LLMsHas used agenerative AImodel for anon-academicpurposeHas traveledinternationallyto attend thisconferenceHas presenteda paper onnaturallanguagegenerationIs currentlyworking on aprojectinvolving cross-lingual transferlearningIs familiarwith theconcept ofpromptengineeringHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel tocreate art ormusicHas apreferred AIresearch toolthey canrecommendHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPHassuccessfullydebugged acomplexLLMHascontributedto an open-source AIprojectIs excitedabout thepotential ofLLMs ineducationCanrecommenda good AI ortech relatedpodcastHasattended anICMLconferencebeforeCan explain thedifferencebetween causaland maskedlanguagemodelsIs optimisticabout thefuture ofhuman-AIcollaborationHas learneda newlanguage inthe last yearKnows atleast threeprogramminglanguagesHas used anLLM tosummarizeresearchpapersCan namethreedifferent LLMarchitecturesHasexperiencewith fine-tuning a pre-trained LLMHasparticipated ina hackathonfocused on AIor LLMs

Human BINGO: Navigating Generative AI and LLMs Across Languages - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Has used a generative AI model for a non-academic purpose
  2. Has traveled internationally to attend this conference
  3. Has presented a paper on natural language generation
  4. Is currently working on a project involving cross-lingual transfer learning
  5. Is familiar with the concept of prompt engineering
  6. Has published research on multilingual LLMs
  7. Has used a generative AI model to create art or music
  8. Has a preferred AI research tool they can recommend
  9. Has collaborated on a research paper with someone from a different continent
  10. Is interested in the ethical implications of generative AI
  11. Has experience with low-resource languages in NLP
  12. Has successfully debugged a complex LLM
  13. Has contributed to an open-source AI project
  14. Is excited about the potential of LLMs in education
  15. Can recommend a good AI or tech related podcast
  16. Has attended an ICML conference before
  17. Can explain the difference between causal and masked language models
  18. Is optimistic about the future of human-AI collaboration
  19. Has learned a new language in the last year
  20. Knows at least three programming languages
  21. Has used an LLM to summarize research papers
  22. Can name three different LLM architectures
  23. Has experience with fine-tuning a pre-trained LLM
  24. Has participated in a hackathon focused on AI or LLMs